D4D(Data for Development) Senegal Challenge Visualisations

Our work is based on an assumption that people tend to make calls, when extraordinary conditions take place. Each antenna’s hourly call volume reproduces a characteristic feature, depending on location, and time. This temporal pattern, high during the day and low at night, resembles a heart electrocardiogram. Our work aims to learn this temporal pattern as normal behaviour of each antenna and predict the possible irregularities as anomalous events. These events may represent crime incidents, public demonstrations, natural disasters, which are crucial for public safety and security. Identifying the severity and location of the event and immediate actions may save lives, especially in developing countries where source of information may not be very reliable.